Andres Arrieta is an Associate Professor in the School of Mechanical Engineering at Purdue University. His research focuses on adaptive structures, mechanical metamaterials, and programmable systems. He holds a PhD from the University of Bristol and conducted postdoctoral research at ETH Zurich. Education: Mechanical Engineer, Universidad de los Andes, 2006 PhD in Mechanical Engineering, University of Bristol, 2010 Postdoctoral Research Fellow, ETH Zurich, 2012 Research Interests: Adaptive Structures Multistable Systems Structural Nonlinearity Robotics & Mechanosensing Origami Engineering Awards: 2019 ASME Best Paper Award 2018 Gary Anderson Early Achievement Award 2012 ETH Postdoctoral Fellowship Labs: Directs the Programmable Structures Lab , exploring smart materials and morphing systems.
Junfei Li is an Assistant Professor in the School of Mechanical Engineering at Purdue University. His research focuses on advanced acoustic technologies, including acoustic tweezers, acoustofluidics, metamaterials, and underwater communication systems. He specializes in multiphysics wave propagation, noise control, and energy harvesting. Li's work bridges fundamental science and engineering applications in biomedical devices, sustainable energy, and advanced materials. Research Interests: Acoustic tweezers for microscale manipulation Design of metamaterials for acoustic control Ultrasound and underwater communication systems Energy-efficient noise mitigation strategies His recent publications emphasize innovations in acoustic metasurfaces, nonreciprocal sound propagation, and biomedical acoustic applications. Li’s research has implications for improving medical imaging, energy sustainability, and next-generation acoustic devices. Awards & Recognition: None explicitly listed in the provided materials. Advising & Grants: No student advisees or grant information specified in the text.
Dorothy Ko is a Professor of Chinese History at Columbia University’s Department of East Asian Languages & Cultures. Her research focuses on the intersection of gender, material culture, and cultural history in premodern China. She holds a PhD from Stanford University and has taught at Barnard College since 2001, previously at Rutgers University. Education: BA, MA, and PhD in History from Stanford University. Research emphasizes women’s roles in economic and cultural development, including domestic artisans, body practices, and Confucian cultures. Notable works include Cinderella Sisters (2005) and The Social Life of Inkstones (2017). Awards include the Joan Kelly Prize and fellowships from the Guggenheim Foundation and Institute for Advanced Study. Teaching includes courses on Chinese cultural history, gender studies, and food history. She has held visiting roles such as the Kluge Chair at the Library of Congress (2022). Research bridges anthropology, history, and women’s studies, highlighting marginalized voices in historical narratives.
Dr. Ryan Carney is an Associate Professor of Digital Science at the University of South Florida's Department of Integrative Biology (College of Arts and Sciences). His research bridges paleontology and epidemiology, using cutting-edge technologies like 3D imaging, AI, and VR/AR. He studies dinosaur biomechanics (e.g., Archaeopteryx flight mechanics) and mosquito-borne diseases (e.g., malaria, Zika) through NSF/NIH-funded collaborations with agencies like NASA and the CDC. His work integrates citizen science platforms (iNaturalist, Mosquito Alert) for disease surveillance and develops AI tools for mosquito classification. Education: PhD (Brown), MPH/MBA (Yale), B.A.'s in Biology & Art (UC Berkeley) Lab: SCA 107 (focuses on digital paleontology and disease modeling) Research interests span dinosaur functional morphology, epidemiological modeling using GIS/remote sensing, and translating science through immersive technologies. He received awards like the National Geographic Emerging Explorer and multiple USF teaching/research accolades. Awards: CAS Liberal Arts Teaching Award, Outstanding Research Achievement, etc. Grants include NSF funding for AI-driven mosquito surveillance and NIH support for disease control. His lab's innovations include the Global Mosquito Observations Dashboard (GMOD) and VR reconstructions of prehistoric species.
Gunnar Kusch is a Senior Research Associate at the Department of Materials Science & Metallurgy, University of Cambridge. His research focuses on defects in semiconductors, porous AlGaN materials, and advanced characterization techniques like cathodoluminescence (CL) and atom probe tomography (APT). He holds a PhD from the University of Strathclyde and leads projects on UV-B LED optimization, nanoscale defect behavior analysis, and semiconductor device design. His work bridges materials synthesis, characterization, and device performance, with applications in energy-efficient lighting and solar cell technology. Key research areas include: Defect engineering in III-nitride semiconductors Porous AlGaN templates for high-efficiency UV emitters Correlative microscopy techniques (CL, EBSD, APT) Composition-structure-property relationships in photovoltaic materials Notable contributions include developing CL-based methods for nanoscale defect analysis and demonstrating improved Cu(In,Ga)S₂ solar cell efficiencies through compositional engineering. His laboratory focuses on translating microscopic insights into macroscopic device improvements.
Dr. Steven H. H. Ding is an Assistant Professor at McGill University's School of Information Studies, specializing in cybersecurity, machine learning, and data mining. His research focuses on AI-driven solutions for malware detection, software vulnerability analysis, and reverse engineering. He holds a PhD from McGill University and has been supported by BlackBerry Cylance and DRDC. His work bridges theoretical advancements with practical applications in military systems and avionics cybersecurity. Dr. Ding earned his PhD in 2019 with notable awards including the FRQNT Doctoral Research Scholarship and McGill's Dean’s Graduate Award. His educational background includes degrees from McGill, Concordia University, and the University of Shanghai for Science and Technology. His research interests span cybersecurity domains such as zero-day malware identification, code obfuscation countermeasures, authorship verification for digital forensics, and AI applications in avionics anomaly detection. He actively contributes to open-source tools like the Kam1n0 MapReduce-based assembly clone search system. Recent work emphasizes adversarial machine learning for evasive malware generation, transformer-based anomaly detection in avionics, and automated SBOM generation for firmware analysis. His publications reflect a focus on real-world cybersecurity challenges in both civilian and defense sectors. Dr. Ding leads the L1NNA Lab and collaborates with industry partners on cutting-edge projects. His contributions include novel techniques for phishing detection leveraging large language models and innovative approaches to reverse engineering software composition in JavaScript applications.
Professor Peter Y. K. Cheung is a Professor of Digital Systems at Imperial College London, holding dual affiliations within the Department of Electrical and Electronic Engineering and the Dyson School of Design Engineering. His work focuses on reconfigurable systems, FPGA architectures, and high-level synthesis tools. He co-founded one of the UK's leading FPGA research groups with Professor Wayne Luk, addressing challenges in variability mitigation, reliability, and application-specific FPGA deployments. His research spans Field-Programmable Gate Arrays (FPGAs) Reconfigurable computing Neural network acceleration Cryptographic protocols Embedded systems He has pioneered techniques such as logic shrinkage for FPGA-based neural networks and developed frameworks like LUTNet for efficient inference. His contributions also include fault-tolerant FPGA designs and methodologies for distributed computation protocols. Key collaborations include work with the Department of Computing on FPGA-based AI acceleration and cybersecurity applications. His recent work explores edge computing, secure decentralized systems, and pandemic modeling using adaptive control strategies. Notable projects include the DSCS protocol for secure distributed computation, acceleration of gravitational wave detection algorithms, and energy-efficient CNN implementations. His research bridges hardware-software co-design with real-world applications in healthcare, finance, and aerospace.
Yuankai (Kenny) Tao is an Associate Professor of Biomedical Engineering at Vanderbilt University's School of Engineering and an SPIE Faculty Fellow. He directs the Graduate Studies program in Biomedical Engineering and leads research in optical imaging systems for clinical diagnostics and therapeutic monitoring in ophthalmology, gastroenterology, and oncology. His lab develops technologies like intraoperative OCT and SECTR, focusing on noninvasive subcellular visualization and biomarker monitoring. Collaborations span engineering, basic sciences, and medicine to translate innovations into clinical tools. Education: Ph.D., Biomedical Engineering, Duke University M.S., Biomedical Engineering, Duke University B.S.E., Biomedical Engineering and Electrical Engineering, Duke University Research Interests: Biomedical optics, optical coherence tomography (OCT), image-guided surgery, therapeutic monitoring, big data analytics, and high-throughput imaging for drug discovery. His work bridges engineering and medicine, emphasizing real-time feedback systems and interdisciplinary innovation. Grants & Labs: Director of the Vanderbilt Institute for Surgery and Engineering (VISE)-affiliated lab, focusing on surgical imaging and translational research. Projects include automated instrument tracking, SECTR systems, and AI-driven imaging analysis. Collaborations involve clinicians and researchers across disciplines.
Wim A Van der Stede is a **Professor of Accounting and Financial Management** at the **London School of Economics (LSE)**, specifically within the **Department of Accounting**. He holds the prestigious **CIMA Professorship** and serves in leadership roles such as LSE Council Member and Houghton Street Ventures Advisory Board member. His research focuses on **management control systems**, **corporate governance**, **executive compensation**, and **performance measurement**, with notable contributions to understanding incentive systems and organizational design. He has authored influential books like *Management Control Systems: Performance Measurement, Evaluation, and Incentives*, translated into multiple languages. Van der Stede’s academic leadership includes editorial roles in top journals like *Management Accounting Research* (Editor-in-Chief 2015–2024), and he has received awards such as the LSE Teaching Excellence Award (2016/17) and the AAA Outstanding International Educator Award (2019). His work integrates empirical studies with practical insights, addressing topics like budgeting, innovation selection, and the impact of information technology on organizations. He actively contributes to global accounting discourse through research, teaching, and advisory roles.
Juan Garay is a Professor in the Department of Computer Science & Engineering at Texas A&M University, affiliated with the College of Engineering. His research focuses on cryptography, information security, and distributed systems, with notable contributions to cryptographic protocols, blockchain technologies, and consensus mechanisms. He holds a leadership role in advancing theoretical and applied aspects of secure computation and network security. Research Interests: Cryptography and Information Security Secure Multiparty Computation Cryptocurrencies and Blockchain Protocols Consensus Algorithms Distributed Computing Game Theory in Cryptography Publications highlight his work on the Bitcoin Backbone Protocol, secure multiparty computation, and post-quantum cryptographic systems. He actively contributes to conferences and workshops in cryptography and distributed systems. He advises graduate students in computer science and engineering, though specific advisee names are not listed. His work is supported by grants from the National Science Foundation (NSF) and other institutions, focusing on secure protocols and distributed systems. Office: Peterson Building (PETR 429) Contact: garay@cse.tamu.edu
Gaetano Valenza is an Associate Professor of Bioengineering at the University of Pisa, Italy, where he leads the Neuro-Cardiovascular Intelligence Lab at the Enrico Piaggio Research Centre. He holds affiliations with the Neuroscience Statistics Research Laboratory at MIT and has served as a Research Fellow at Harvard Medical School and Massachusetts General Hospital. His academic work spans bioengineering, computational physiology, and affective computing. His research focuses on statistical and nonlinear biomedical signal and image processing , cardiovascular and neural modeling , and physiologically interpretable artificial intelligence . He develops wearable systems for physiological monitoring, with applications in autonomic nervous system assessment, brain-heart interactions, and mental health. His work has led to novel metrics such as the Sympathetic and Parasympathetic activity indices derived from ECG. The 15 most recent publications reflect a consistent trend in brain-heart interplay , complexity analysis of physiological signals , explainable AI in healthcare , and virtual reality applications in mental health . His work integrates advanced signal processing, nonlinear dynamics, and machine learning to decode emotional and cognitive states from physiological data. Dr. Valenza is a Senior Member of IEEE and serves on several technical committees. He is an active editorial leader, currently serving as Associate Editor for IEEE-EMBC , Plos One , Complexity , and Scientific Reports , and has guest-edited special issues in Philosophical Transactions of the Royal Society A and IEEE Journal of Biomedical and Health Informatics . He has led or participated in numerous international research projects, including FP7 and H2020 initiatives such as NEVERMIND and EXPERIENCE. He teaches courses in Biostatistics, Probability & Biostatistics, and Advanced Image Processing at the University of Pisa. As lab head and project coordinator, he leads a multidisciplinary team working on neuro-cardiovascular intelligence, wearable systems, and AI-driven mental health interventions.
Pablo Fajardo Peña is a Full Professor in the Department of Aerospace Engineering at Universidad Carlos III de Madrid (UC3M). He leads the Plasmas and Space Propulsion Team (EP2) and co-directs the Aerospace Engineering Research Group. His research focuses on advanced propulsion technologies for space applications, including plasma thrusters, electric propulsion, and fluid-thermal systems. Professor Peña's work spans computational modeling of plasma dynamics, experimental characterization of propulsion systems, and development of novel thrusters like Hall effect thrusters and electrospray systems. His recent publications analyze plasma discharge mechanisms, thruster plume behavior, magnetic nozzle effects, and propellant interactions. He leads multiple EU and Spanish-funded projects including HIPATIA (Helicon Plasma Thruster), CHEOPS (Hall Effect Orbital Propulsion), and ADAPT (Advanced Plasma Propulsion). These initiatives focus on developing efficient propulsion systems for spacecraft and addressing challenges in space debris removal. Professor Peña supervises doctoral research on plasma diagnostics and thruster simulation, and has developed simulation tools like HYPHEN (Hybrid Plasma Thruster Holistic Environment). His team collaborates with ESA, Airbus, and SENER Aeroespacial on propulsion technology validation.
Prof. Dr. Amelie Hagelauer holds a professorship in Micro- and Nanosystem Technology at the TUM School of Computation, Information and Technology, Technical University of Munich. Her work focuses on advanced electronics and systems integration across quantum computing hardware, resistive memory technologies, and high-frequency RF systems. She has contributed to innovations in superconducting qubit readout architectures, multi-level RRAM designs, and 3D-integrated CMOS-compatible quantum devices. Research interests span quantum hardware design, nanoelectronic devices, RF front-end systems, and emerging memory technologies. Her work emphasizes practical implementation challenges such as low-power operation, high-voltage handling in RF switches, and wafer-scale fabrication processes. Recent projects include D-band radar systems, energy-efficient 60 GHz transceivers, and antenna tuning solutions for 5G applications. Publications from 2023-2025 showcase advancements in resistive switching device characterization, mitigation of TLS losses in superconducting qubits, and reconfigurable AI accelerators using RRAM-based digital twins. Her work bridges theoretical device physics with practical integrated circuit design, addressing scalability and reliability in next-gen electronics. Awards and grants: None explicitly listed in provided texts. Active collaborations include EU-funded projects on quantum computing platforms and TUM's Electronic Photonic Integration initiatives. Leads research teams in microsystem technology with emphasis on cross-disciplinary approaches combining CMOS processes, MEMS, and quantum engineering.
Prof. Dr. Johannes Sauer is a Professor at the Technical University of Munich (TUM), holding dual affiliations with the TUM School of Management and the TUM School of Life Sciences . His academic focus is on production and resource economics, with expertise in agricultural sustainability, policy evaluation, and circular economy strategies in Asia-Pacific and Latin America. Education: Bachelor’s/Master’s in Agricultural Economics from Universities of Tübingen, Hamburg, and Imperial College London. Doctorate (summa cum laude) in Agricultural Economics from the University of Bonn (2004). Research Interests: Prof. Sauer’s work spans productivity and resilience in agricultural systems, adoption of sustainable technologies, water resource valuation, and bioeconomic trends. He emphasizes smart technologies and circular economy applications in developing regions. His research employs econometric methods to analyze policy impacts and environmental-economic trade-offs. Key Trends in Publications: Recent articles highlight climate-smart agriculture, ICT adoption in rural China, and agroforestry’s role in reducing ecological-economic trade-offs. He explores behavioral drivers of policy participation and innovative tools like the IoFarm decision support system. Awards: 2021 Honorary Professorship at ANU OECD Fellow Awards (2010, 2016) Best Paper Awards (2008–2015) Consulting & Roles: OECD and Asian Development Bank consultant, ESRC Peer Review College member, and liaison lecturer for the German National Academic Foundation. He advises on agri-environmental policies and international development. Labs/Teams: Active in collaborative projects such as PONDERFUL Framework and IPM Popilia , focusing on nexus research and pest management strategies.
Charles A. Bouman is the Showalter Professor of Electrical and Computer Engineering and Biomedical Engineering at Purdue University, with a courtesy appointment in Mathematics. He is a leading researcher in computational imaging, integrating statistical signal processing, physics, and computation for applications in healthcare, scientific, and industrial imaging. Education: B.S.E.E., University of Pennsylvania, 1981 M.S., University of California at Berkeley, 1982 Ph.D. in Electrical Engineering, Princeton University, 1989 His research focuses on computational imaging , including statistical image models, multiscale techniques, tomographic reconstruction, and fast algorithms. Key areas include Model-Based Iterative Reconstruction (MBIR), Plug-and-Play priors, document processing, and multiscale segmentation. His work has led to foundational contributions in total variation regularization and sparse-view reconstruction. The recent publications highlight a strong trend in integrating machine learning with physical models for image reconstruction, particularly through Plug-and-Play methods. His work spans optical tomography, halftoning, image scaling, and document compression, demonstrating consistent innovation in both theory and practical software implementation. Scientific Awards and Honors: Member, National Academy of Inventors Life Fellow, IEEE Fellow, IS&T; Honorary Member (2022); Service Award (2023) Fellow, SPIE and AIMBE IEEE Signal Processing Society Claude Shannon-Harry Nyquist Award (2021) Electronic Imaging Scientist of the Year (2014) SIAM Imaging Science Best Paper Prize (2020) Founder, IS&T Computational Imaging Conference (2003) Co-Founder, IEEE Transactions on Computational Imaging Vice President, IS&T; Former VP of Publications (2000–2004) Bouman has advised numerous graduate students and leads a vibrant research group developing open-source tools like MBIRJAX , SVMBIR , and OpenMBIR . His research has been supported by the National Science Foundation, General Electric, Intel, Xerox, Hewlett-Packard, and the State of Indiana 21st Century Fund. He maintains an active presence through tutorials, conference leadership, and educational resources including video lectures and a textbook on Foundations of Computational Imaging. Labs and Research Teams: His group develops cutting-edge software for tomographic reconstruction, clustering, segmentation, and dynamic sampling. Projects include Gaussian Mixture modeling (GMCluster), Plug-and-Play implementations, Sparse Matrix Transforms, and UAV sensing datasets. The research is highly interdisciplinary, bridging engineering, mathematics, and biomedical applications.
